Quality control method of ground temperature observation material

Abstract

The invention discloses a quality control method of a ground temperature observation material. The method includes the following steps: firstly acquiring temperature data of a meteorological station within an object region, then resolving an experimental variance function value, and using an arctan function that is proposed to carry out fitting on the experimental variance function value, then resolving the weight of each neighboring meteorological station to an object meteorological station by using a Kriging equation set, further using gradient Kriging method to estimate the temperature values of respective meteorological station and evaluate the precision of the temperature values, and finally conduct threshold examination on a temperature estimation value and an original observation value so as to determine whether the data is right or not and correct the data accordingly. According to the invention, the method addresses the problems of insufficient consideration of impact of space distribution, temperature space relativity and variance thereof and landform on temperature of current quality control methods.

Description

technical field [0001] The invention belongs to the technical field of meteorological observation, and in particular relates to a quality control method for surface air temperature observation data. Background technique [0002] Meteorological data quality control refers to the data review of meteorological observation stations and data centers in order to find missing or wrong data and supplement or correct them, so as to ensure the maximum completeness and accuracy of the data. Since surface observation data can provide more accurate atmospheric characteristics such as dynamics, thermal conditions, and humidity distribution near the surface of the atmosphere, the development of surface data assimilation technology is one of the important methods to improve the level of numerical weather prediction, and the development of data assimilation technology The primary task is how to use quality control methods to obtain high-quality observation data, and high-quality surface mete...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the technical problems raised by the above-mentioned background technology, the present invention aims to provide a quality control method for surface air temperature observation data, which solves the impact of the inverse distance weighting method on the spatial distribution of adjacent observation stations, the spatial correlation of air temperature and its variability, and the impact of terrain on air temperature. Issues that affect under-consideration

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